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Direct assessment of the hemodynamic severity of RAS has yet to be addressed. In this work, we present a computational concept to derive a new, noninvasive, and patient\u2010specific index to assess the hemodynamic severity of RAS and predict the potential benefit to the patient from a stenting therapy. The hemodynamic index is derived from a functional relation between the translesional pressure indicator (TPI) and lumen volume reduction (S) through a parametric deterioration of the RAS. Our in\u2010house computational platform, <jats:italic>InVascular<\/jats:italic>, for image\u2010based computational hemodynamics is used to compute the TPI at given <jats:italic>S<\/jats:italic>. <jats:italic>InVascular<\/jats:italic> integrates unified computational modeling for both image processing and computational hemodynamics with graphic processing unit parallel computing technology. The TPI\u2013S curve reveals a pair of thresholds of <jats:italic>S<\/jats:italic> indicating mild or severe RAS. The TPI at <jats:italic>S\u00a0=\u00a00<\/jats:italic> represents the pressure improvement following a successful stenting therapy. Six patient cases with a total of 6 aortic and 12 renal arteries are studied. The computed blood pressure waveforms have good agreements with the in vivo measured ones and the systolic pressure is statistical equivalence to the in\u2010vivo measurements with <jats:italic>p<\/jats:italic>\u2009&lt;\u2009.001. Uncertainty quantification provides the reliability of the computed pressure through the corresponding 95% confidence interval. The severity assessments of RAS in four cases are consistent with the medical practice. The preliminary results inspire a more sophisticated investigation for real medical insights of the new index. This computational concept can be applied to other arterial stenoses such as iliac stenosis. Such a noninvasive and patient\u2010specific hemodynamic index has the potential to aid in the clinical decision\u2010making of interventional treatment with reduced medical cost and patient risks.<\/jats:p>","DOI":"10.1002\/cnm.3611","type":"journal-article","created":{"date-parts":[[2022,5,5]],"date-time":"2022-05-05T05:49:14Z","timestamp":1651729754000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A new noninvasive and patient\u2010specific hemodynamic index for the severity of renal stenosis and outcome of interventional treatment"],"prefix":"10.1002","volume":"38","author":[{"given":"Huidan","family":"Yu","sequence":"first","affiliation":[{"name":"Department of Mechanical and Energy Engineering Indiana University\u2010Purdue University, Indianapolis (IUPUI)  Indianapolis Indiana USA"},{"name":"Department of Surgery Indiana University School of Medicine  Indianapolis Indiana 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